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Assignment Advanced Regression - House price prediction

Outline a brief description of your project. Assignment Part-I A US-based housing company named Surprise Housing has decided to enter the Australian market. The company uses data analytics to purchase houses at a price below their actual values and flip them on at a higher price. For the same purpose, the company has collected a data set from the sale of houses in Australia. The data is provided in the CSV file below.

The company is looking at prospective properties to buy to enter the market. You are required to build a regression model using regularisation in order to predict the actual value of the prospective properties and decide whether to invest in them or not.

The company wants to know:

Which variables are significant in predicting the price of a house, and

How well those variables describe the price of a house.

Also, determine the optimal value of lambda for ridge and lasso regression.

Table of Contents

General Information

  • Provide general information about your project here.
  • What is the background of your project?
  • What is the business probem that your project is trying to solve?
  • What is the dataset that is being used?

Conclusions

  • Conclusion 1 from the analysis
  • Conclusion 2 from the analysis
  • Conclusion 3 from the analysis
  • Conclusion 4 from the analysis

Technologies Used

  • library - version 1.0
  • library - version 2.0
  • library - version 3.0

Acknowledgements

Give credit here.

  • This project was inspired by...
  • References if any...
  • This project was based on this tutorial.

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Created by [@sreenp] - feel free to contact me!

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